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import json
import os
from tqdm import tqdm
from datasets import Dataset, load_dataset, Image
def load_jsonl(file_path):
"""
Loads a JSONL file and returns a list of Python dictionaries.
Each dictionary represents a JSON object from a line in the file.
"""
data = []
with open(file_path, 'r', encoding='utf-8') as f:
for line in f:
try:
# Parse each line as a JSON object
json_object = json.loads(line.strip())
data.append(json_object)
except json.JSONDecodeError as e:
print(f"Error decoding JSON on line: {line.strip()} - {e}")
return data
def main():
dset = "val"
workdir = "./coco"
# Load Annotions from Official Coco
with open(
os.path.join(workdir, "annotations", f"captions_{dset}2017.json"),
"r",
encoding="utf-8"
) as reader:
data = json.load(reader)
# Format dict of image elements
images = {}
for item in tqdm(data["images"]):
_idx = item["id"]
images[_idx] = {
"file_name": item["file_name"],
"height": item["height"],
"width": item["width"],
"id": _idx,
"image": os.path.join(workdir, f"{dset}2017", item["file_name"]),
"captions": [],
"narratives": []
}
# Assign official annotations
for item in tqdm(data["annotations"]):
_idx = item["image_id"]
images[_idx]["captions"].append(item["caption"])
# Load Narratives
data_narr = load_jsonl(os.path.join(workdir, "localized_narratives", f"coco_{dset}_captions.jsonl"))
for item in tqdm(data_narr):
_idx = int(item["image_id"])
images[_idx]["narratives"].append(item["caption"])
def gen():
for k, v in images.items():
yield v
ds = Dataset.from_generator(gen)
ds = ds.cast_column("image", Image())
ds.save_to_disk(f"coco/datasets/data/{dset}", max_shard_size="400MB")
return
def test_coco():
ds = load_dataset("./coco/datasets", split="val")
print(ds.info)
if __name__ == "__main__":
# main()
test_coco()
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